Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation.

Abstract

Authors

• Seul Bi Lee
  Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
• Youngtaek Hong
  CONNECT-AI R&D Center, Yonsei University College of Medicine.
• Yeon Jin Cho
• Dawun Jeong
• Jina Lee
  Microbiology and Functionality Research Group, World Institute of Kimchi, Gwangju 61755, Republic of Korea.
• Soon Ho Yoon
  Department of Radiology, Seoul National College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea (H.C., S.H.Y., S.J.P., C.M.P., J.H.L., H. Kim, E.J.H., S.J.Y., J.G.N., C.H.L., J.M.G.); CHESS Center, The First Hospital of Lanzhou University, Lanzhou, China (Q.X., J.L.); Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea (K.H.L.); Department of Internal Medicine, Incheon Medical Center, Incheon, Korea (J.Y.K.); Department of Radiology, Seoul Medical Center, Seoul, Korea (Y.K.L.); Department of Radiology, National Medical Center, Seoul, Korea (H. Ko); Department of Radiology, Myongji Hospital, Gyeonggi-do, Korea (K.H.K.); and Department of Radiology, Chonnam National University Hospital, Gwanju, Korea (Y.H.K.).
• Seunghyun Lee
  Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA. Electronic address: seunghyun.lee.22@gmail.com.
• Young Hun Choi
  Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea. iater@snu.ac.kr.
• Jung-Eun Cheon
  Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.

Keywords

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